The diagnostic imaging which is implemented using images including single photon emission computed tomography (hereinafter referred to as “SPECT”) images, positron emission tomography (hereinafter referred to as “PET”) images, magnetic resonance imaging (hereinafter referred to as “MRI”) images, and x-ray computed tomography (hereinafter referred to as “CT”) images can obtain information about a lesioned part existing in a body of a subject in a nondestructive manner. Therefore, the diagnostic imaging is essential to the current medical diagnosis.
Various studies have been conducted heretofore on the diagnostic imaging technology and in recent years the technology of imaging which obtain not only morphologic information of a part in a living body but also functional information of the living body has been developed and is clinically applied. For example, the functional magnetic resonance imaging tomography (hereinafter referred to as “fMRI”) for imaging a local change in blood flow in a brain by using the nuclear magnetic resonance, and nuclear medicine such as SPECT and PET were developed and is clinically applied.
Such functional images are images obtained by imaging a functional change in a living body and a lesion. Therefore, the functional images have the advantage of high specificity for detection of a lesioned part. On the other hand, the functional images also have the disadvantage of lacking anatomical position information of the lesioned part.
A fused image is used for the purpose of compensating for the disadvantage of the functional images. The fused image is an image obtained by overlapping a functional image and a morphologic image. This fused image permits us to confirm an anatomical position of the lesioned part detected in the functional image, on the morphologic image. Therefore, the fused image is useful for definite diagnosis, determination of therapeutic strategy, and so on.
The fused image can be created from images originating in such different modalities, i.e., images acquired by different devices, and also from images originating in the same modality. For example, when the fused image is one based on a plurality of nuclear medicine images obtained by executing the same inspection multiple times, we can obtain, for instance, a change in value at the same part, different pieces of blood flow information from the same part, or a receptor distribution.
Reflecting the increase in such needs for the fused image, a variety of methods have been proposed and developed heretofore for automatically creating the fused image. For example, the Automatic Multimodality Image Registration method (hereinafter referred to as the AMIR method) (cf. Non-patent Document 1), the AC-PC line alignment method (cf. Non-patent Document 2), the mutual information maximization method (cf. Non-patent Document 3), and others have been developed and put to practical use.
Non-patent Document 1: Babak A. Ardekani et al., “A Fully Automatic Multimodality Image Registration Algorithm,” Journal of Computer Assisted Tomography, (USA), 1995, 19, 4, p 615-623
Non-patent Document 2: “Dr. View/LINUX User Manual (ver. 3),” AJS (Asahikasei Joho System) Inc., p. 466-470
Non-patent Document 3: F. Maes et al., “Multimodality Image Registration by Maximization of Mutual Information,” IEEE Transactions on Medical Imaging, (USA), 1997, 16, 2, p 187-198